check_eligibilityCheck whether we can return quotes for a state before any personal details are collected. Call this first. Returns the states we are licensed in, what we can do in each, and how many licensed agents can take a request there.
| Name | Required | Description | Default |
|---|---|---|---|
| state | No | Two-letter US state code, e.g. NV | |
| product | Yes | auto |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds meaningful context beyond that: no personal details are needed, it should be called first, and it returns licensing status, allowed actions, and licensed agent counts. This goes beyond the safety profile captured by annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, each earning its place: purpose, call ordering, and return contents. No filler or redundant restating of the tool name or schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only eligibility check with annotations covering safety and no output schema, the description gives enough information for an agent to know when to call it and what to expect. The only minor gap is lack of detail about optional parameters, but this does not undermine usability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50%, and the description does not add parameter-level detail beyond what the schema already provides. The product parameter is explained by its enum/default, and state has a schema description, so the description's omission is not critical, but it also does not clarify behavior when state is omitted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource: checking eligibility for returning quotes, explicitly before personal details are collected. It also differentiates from likely siblings like get_quotes by positioning itself as the upfront availability check and specifying the returned data: states, capabilities, and agent counts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'Call this first' is clear, direct guidance that establishes sequencing relative to later steps. It gives a clear context for use—before personal details are collected—but does not explicitly name alternative tools or conditions where another sibling should be chosen instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool covers a distinct function: eligibility, quoting, consent terms, agency registration/status, lead pulling, market data, and agent contact. The only mild overlap is between check_eligibility and get_quotes, but their descriptions make clear one is a pre-check for licensing/state capacity while the other returns actual indicative prices.
Names are uniformly snake_case and mostly follow a verb_noun pattern like check_eligibility, get_quotes, pull_requests, register_agency, and request_agent_contact. However, agency_status, data_use_terms, and market_data are noun phrases rather than actions, so the pattern is mixed but still readable.
Eight tools is well-scoped for this insurance-agency lead and quote platform. Each tool earns its place in the workflow, with no redundant sprawl and no feeling of an underbuilt or overloaded surface.
The primary flow is covered: eligibility, quoting, consent, agent contact, agency registration/status, lead pulling, and market data. Missing lifecycle operations include updating an agency registration, managing credits/payments, and an explicit consent-revocation tool, since POST /forget is referenced but not exposed as an MCP tool.